Quotas and qualications

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Quotas and qualications: the impact of gender quota
laws on the qualications of legislators in the Italian
parliament
Ana Catalano Weeks and Lisa Baldez
European Political Science Review / Volume 7 / Issue 01 / February 2015, pp 119 - 144
DOI: 10.1017/S1755773914000095, Published online: 09 April 2014
Link to this article: http://journals.cambridge.org/abstract_S1755773914000095
How to cite this article:
Ana Catalano Weeks and Lisa Baldez (2015). Quotas and qualications: the impact of gender
quota laws on the qualications of legislators in the Italian parliament. European Political Science
Review, 7, pp 119-144 doi:10.1017/S1755773914000095
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Quotas and qualifications: the impact
of gender quota laws on the qualifications
of legislators in the Italian parliament
A N A C A T A L A N O W E E K S
1
A N D L I S A B A L D E Z
2
*
1
Department of Government, Harvard University, Cambridge Street, Cambridge, MA, USA
2
Department of Government, Dartmouth College, Silsby Hall, Hanover, NH, USA
This article addresses concerns that candidates nominated because of gender quota laws will
be less qualified for office. While questions of candidate quality have long been relevant to
legislative behavior, quota laws requiring a certain percentage of candidates for national office
to be women have generated renewed interest. Gender quotas are often perceived to reduce
the scope of political competition. By putting gender identity center stage, they preclude the
possibility that elections will be based on ‘ideas’ or ‘merit’ alone. Other electoral rules that
restrict candidate selection, such as the centralization of candidate selection common in closed
list PR systems, have been found to reduce the quality of candidates. Rules that open selection,
such as primaries, result in higher quality candidates. We exploit the institutional design of
Italy’s mixed electoral system in 1994, where quotas were applied only to the PR portion of the
list, to compare the qualifications of men, women, and ‘quota women’. We estimate regressions
on several measures of deputies’ qualifications for office and performance in office. We find that
unlike other rules limiting candidate selection, quotas are not associated with lower quality on
most measures of qualifications. In fact, quota women have more local government experience
than other legislators and lower rates of absenteeism than their male counterparts. Contrary to
critics, quota laws may have a positive impact on legislator quality. Once the quota law was
rescinded, quota women were less likely to be re-elected than non-quota women or men, which
suggests that discrimination – not qualification – limits women’s status as candidates.
Keywords: Italy; gender quotas; qualifications; legislatures
Introduction
This article addresses concerns that candidates nominated because of gender quota
laws will be less qualified. While questions of candidate quality have long been
relevant to legislative behavior, quota laws, which require women to comprise a
certain percentage of candidates for national office, have generated a new wave of
interest. Gender quotas are often perceived to reduce the scope of political competition.
Parliaments in 47 countries have adopted laws that require women to comprise a
certain percentage of candidates for national office (International IDEA, 2013).1
* E-mails: catalan@fas.harvard.edu; lisa.baldez@dartmouth.edu
1
The rise of legislative gender quotas is part of a larger quota phenomenon, including voluntary
political party quotas in over 100 countries and reserved seats for women, which mandate the election of
women to a certain number of seats, in ~ 20 countries (quotaproject.org).
European Political Science Review (2015), 7:1, 119–144 © European Consortium for Political Research
doi:10.1017/S1755773914000095
First published online 9 April 2014
119

By putting gender identity center stage, quotas preclude the possibility that elections
will be based on ‘ideas’ or ‘merit’ alone. Other electoral rules that restrict candidate
selection, such as the centralization of candidate selection common in closed list PR
systems, have been found to reduce the quality of candidates (Carey and Shugart,
1994; Gagliarducci et al., 2011), while rules that open up selection, such as
primaries, result in higher quality candidates (Carey and Polga-Hecimovich, 2006;
Hirano and Snyder, 2013). We exploit the institutional design of Italy’s mixed
electoral system in 1994, where quotas were applied only to the PR portion of
the list (closed-list) to compare the qualifications of men, women, and ‘quota
women’. Using data from a mixed electoral system allows us to determine whether
women who were selected under a quota differ from those who were not.
We estimate regressions on several measures of deputies’ qualifications for office.
We include performance in office as a measure of candidate qualifications,
exploiting available data to generate an ex post measure of qualifications.
We find that unlike other rules limiting candidate selection, quotas are not
associated with lower quality on most measures of qualifications. On the contrary:
quota women may have improved the overall level of qualifications. Quota women
are 5% more likely to have local government experience than other representatives.
Quota women show up for work more than their male counterparts: they attend
legislative sessions 7% more than men elected to PR seats. Once the quota law was
rescinded, quota women are less likely to be re-elected than non-quota women or
men. To the extent that we regard re-election as a clean indicator of performance,
this result is troubling as it might suggest that voters repudiated quota women.
In Italy, however, it was not voters but party leaders who determined the re-election
prospects of quota women. With the quota gone, party leaders buried female can-
didates deep on their electoral lists in 1996. Our results thus suggest that dis-
crimination by party leaders – not qualifications – explains the lower numbers of
women nominated for office once the quota was gone.
Theoretical background: who is qualified to run for office?
What does it mean to be qualified for political office? If an assembly is to be
‘an exact portrait of the people at large’, as American founding father John
Adams urged, then everyone is equally capable of representing the people. None-
theless, when critics suggest that gender quotas will result in the election of
unqualified candidates, they have in mind a specific set of characteristics, many of
which are captured by political science research. The literature on challenger
quality, political ambition, and gender quotas offers a range of possible measures
of qualifications. Our analysis takes these characteristics at face value; we offer a
more critical perspective on qualifications in the conclusion. We developed our
measures on the basis of empirical relevance (i.e., the concept of qualifications must
be measurable and not only theoretical) and frequency of citation, as described
in Table 1.
120 A N A C A T A L A N O W E E K S A N D L I S A B A L D E Z

Table 1. Identifying common formulations of qualifications for political office
Ever held elective office Occupation (type/status) Campaign spending Honesty /integrity Education Fame/recognition Google citations
Challenger quality
Jacobson and Kernell (1981) ✓ 779
Green and Krasno (1988)a
✓ ✓ ✓ ✓ 437
Jacobson (1989) ✓ 243
Bond et al. (1985) ✓ ✓ 209
Caselli and Morelli (2001) ✓ ✓ 184
Abramowitz (1991) ✓ ✓ ✓ ✓ 179
Stone et al. (2004)b
✓ ✓ ✓ ✓ ✓ 80
McCurley and Mondak (1995)c
✓ 79
Squire (1992)d
✓ 79
Shugart et al. (2005)e
✓ 63
Backgrounds/ambition
Putnam (1976) ✓ ✓ 798
Schlesinger (1966) ✓ ✓ 458
Carroll (1994)f
✓ ✓ ✓ 404
Loewenberg and Patterson (1979)g
✓ 302
Burrell (1994)h
✓ ✓ ✓ 270
Norris (1997)i
✓ ✓ ✓ 217
Canon (1990) ✓ ✓ ✓ 152
Fox and Lawless (2004)j
✓ 132
Gender quotas
Besley et al. (2005) ✓ ✓ 64
Bird (2003)k
✓ ✓ ✓ 31
Murray (2010)l
✓ ✓ 7
Total 15 11 4 6 7 4
a
Green and Krasno also use ever running for elective office and political activism as measures of qualification.
b
Stone et al. also include problem-solving ability, public speaking, dedication to public service, grasp of issues, and performance in office as measures of quality (all are survey-based).
c
McCurley and Mondak also use a measure of perceived competence (survey-based).
d
Squire also employs a measure of campaign skills, for example public speaking, derived from media reports.
e
Shugart et al. also use birthplace in the district nominated as a measure of qualification.
f
Carroll also measures party activity, organizational activity, and campaign resources/planning.
g
Loewenberg and Patterson also include social class and interest group affiliations.
h
Burrell also includes party and civic activity, marital status, and children.
i
Norris also includes age, class, and ambition.
j
Fox and Lawless consider a range of other personal characteristics, including political attitudes and experience, family responsibilities, and self-perceived qualifications.
k
Bird also assesses family connections to politics, household income levels, age, children at home, and political party membership.
l
Murray also includes age as a measure of qualification.
Quotasandqualifications121

We found that the six most common formulations of qualifications are previous
experience in elective office, occupational type or status, campaign spending, honesty or
integrity, education, and fame or recognition. Of these, previous experience in elective
office is the most prevalent by far. Political experience is sometimes seen as a proxy for
many ‘good’ qualities, like charisma and campaign skills, which are demonstrated by
virtue of the individual’s success in previous elections (Squire, 1995). It can also be
interpreted as an indicator of the candidate’s ability to perform the duties of office in the
future, because those who have held office before are thought to accumulate practical
skills and a relevant knowledge base (Carroll, 1994).
Occupation and education are the next most common definitions of qualifica-
tions. The social backgrounds literature has found that legislators consistently have
higher-status occupations and are better educated than the average citizen (Putnam,
1976). Educational credentials are frequently viewed as measures of competence for
holding national office (Burrell, 1994), and a high status occupation signifies success
in the business, civic, or professional world that voters use as an indicator of future
performance in office (Carroll, 1994).
In this study we are interested in measuring both the characteristics that define
‘good’ candidates for legislative office, and the characteristics that define the
behavior of ‘good’ legislators once they are in office. We follow recent literature in
defining three characteristics of performance in office. The number of bills intro-
duced is a basic and frequently used measure of legislator output (see Ferraz
and Finan, 2008; Gagliarducci et al., 2008; Anzia and Berry, 2011). Legislators
introduce bills to communicate their commitment on a particular issue to their
constituents and to party leaders. Introducing no bills can be seen as an indicator of
low quality, even if institutional constraints limit opportunities to do so. Another
common indicator of legislator quality is absenteeism (see Gagliarducci et al., 2011;
Galasso and Nannicini, 2011). Elected officials must show up for legislative sessions
and vote in order to represent constituents effectively. Finally, re-election is perhaps
the ultimate measure of legislator quality (see Diermeier et al., 2005; Keane and
Merlo, 2007). According to our model, less qualified candidates introduce fewer
bills, show up less frequently to work, and are re-elected less often than their
non-quota peers. We explain how we operationalize these three measures of
qualifications (previous political experience, occupation, and education) and three
measures of quality in office (bills proposed, absenteeism, and re-election) in the
Data and Methods section.
Research has established a strong link between the implementation of gender
quotas and an increase in the percentage of women elected to office, contingent on
how the quota is designed and how it interacts with the electoral system (Jones,
1996, 1998, 2004; Jones and Navia, 1999; Meier, 2004; Norris, 2004; Schmidt and
Saunders, 2004; Dahlerup and Freidenvall, 2005; Squires, 2005; Dahlerup, 2006;
Matland, 2006; Baldez, 2007; Tripp and Kang, 2008; Krook, 2009; Schwindt-
Bayer, 2009; Hughes, 2011). Research examining the impact of quotas on sub-
stantive representation focuses on the qualifications that candidates bring to office,

their behavior in office, and attitudes toward various issues. Legislative quota
policies often apply to all female candidates, so that all women elected effectively
become ‘quota women’.
This study adds new dimensions to the growing literature on the impact of gender
quotas by focusing on the impact of quotas on candidate qualifications and by
examining the impact of quotas as distinct from gender. Most of the literature on
the substantive effect of gender quotas reflects this, examining cases in which quotas
apply to all of the female candidates and none of the men (Childs, 2002; Htun and
Jones, 2002; Bird, 2003; Cowley and Childs, 2003; Schwartz, 2005; Sater, 2007;
Franceschet and Piscopo, 2008; Zetterberg, 2008; Júlio and Tavares, 2010). These
studies make it impossible to determine whether the observed effects derive from
differences between men and women, or from the presence of a quota. We compare
men to quota women and non-quota women, taking advantage of data from Italy’s
mixed electoral system and a one-time application of gender quotas in the 1994
parliamentary elections. Our analysis thus allows us to determine whether women
who were selected under a quota differ from those who were not. Our approach
builds on the work of a handful of scholars who isolate the impact of a quota on
candidate qualifications (Chattopadhyay and Duflo, 2004; Besley et al., 2005;
Murray, 2010; O’Brien, 2012).
Case selection: why Italy?
To test assumptions about gender quotas and qualifications, we use data about
members of the Italian Camera dei Deputati (House of Representatives) elected in
1994.2
During this period, Italy had just undergone a major change to its political
system, triggered by a 2-year investigation of widespread political bribery. The mani
pulite (clean hands) scandal exposed illegal patronage and kickbacks for government
contracts involving all of Italy’s major political parties. As a result, in June 1993,
Italians voted in a referendum to change the electoral system from a proportional
system to a mixed-member system, whereby 75% of representatives were elected via a
majoritarian system and 25% via a proportional system. In the majoritarian tier,
members of parliament were elected in single-member districts (SMDs) with simple
plurality voting. In the proportional tier, they were elected from closed party lists at the
regional level (Bartolini and D’Alimonte, 1996; Bartolini et al., 2004).
Capitalizing on the wave of reforms in the early 1990s, women representatives
from the center-left coalition introduced a bill designed to ensure adequate repre-
sentation of women on party lists. The quota proposal gave rise to a lively debate,
both in parliament and in the broader public. Advocates claimed that adopting a
gender quota would mitigate the negative effects that a majoritarian system would
have on women’s representation. Opponents argued that the quota entailed an
2
The quota law did not apply to the Senate, so we do not include it in the analysis.
Quotas and qualifications 123

unnecessary form of protectionism and would result in electing less qualiﬁed
women to ofﬁce (Guadagnini, 2005). While controversial, the quota legislation
passed into law in August 1993.3
The law stipulated that candidates in the pro-
portional tier would be listed in alternate order on the party lists according to
gender, a practice known as ‘zipping’.4
In the pre-quota era, all seats were elected by PR. In 1992, women held 8% of
seats. After the implementation of the quota law, the percentage of women elected
to the Chamber of Deputies reached an unprecedented level, nearly doubling from
8% (51 women of 630 total seats) in 1992 to 15% (92 women) in 1994 (see
Figure 1). There were two tiers in the 1994 election, one (PR) with gender quotas
and the other (SMD) with no gender quotas. On the quota side, women won 32% of
Figure 1 Number of women elected to the Italian Parliament by electoral system, 1992–96.
3
Law no. 277 of August 4, 1993: ‘New regulations for the election of the Chamber of Deputies’.
4
The law includes a clause (Art. 2) stating that for the 155 PR seats, lists should consist of candidates of
both sexes in alternate order. The text reads: ‘Qualora una lista sia stata formata da candidate e da can-
didate, I medesimi devono essere elencati in ordine alternato sia sul manifesto contenente le liste dei can-
didate della circoscrizione che sulle schede di votazione’. We translate this as, ‘For the PR lists, male and
female candidates must be listed in alternating order on both the manifesto containing the lists of candidates
for the constituency and on the ballots’.

the seats. On the SMD side, women won 9% of the seats.5
In 1995, the Constitutional
Court declared the quota law unconstitutional and the legislature repealed it before the
next election. Without the quota, the total percentage of women elected in the 1996
elections fell to 11% (71 women). More than half of the gains for women in the PR tier
were lost; the percentage of women dropped from 32% to 19%. The percentage of
women elected in the majoritarian tier remained around 9%.
The one-time quota policy in Italy is an instructive case to analyze the qualifica-
tions issue because it allows us to distinguish quota women from non-quota women,
as well as to compare them with men, addressing the lacuna we discuss above. The
numbers are small, but analyzing differences within the 12th parliament (1994–96),
as opposed to a before and after analysis, has the added advantage of avoiding
biases from comparisons over time that could be the result of other factors specific
to particular elections. Evaluating men, women, and quota women within the same
legislative term allows us to hold constant many factors that could potentially
change after a quota policy has been implemented, such as party selection procedures
or voter preferences.
Ideally, we might like to bolster our results by using a ‘difference-in-differences’
research design to compare female representatives’ qualifications across the differ-
ent types of electoral system before and after the quota law was implemented. Like
our strategy, this method also avoids contamination by extraneous factors (a problem
with simple pre-post designs). In addition, the double difference would provide a more
plausible estimate of the impact of the quota law compared with findings based on a
single, ‘between groups’ difference because it would account for selection bias. In our
case, women elected in the PR tier may tend to be different from those elected in
the majoritarian tier even in the absence of the quota law.6
Unfortunately, such an
analysis is not possible in the Italian case because the quota law was introduced at the
same time as a change in the electoral system. Before quotas were implemented,
all representatives were elected via proportional representation. In order to account for
this, we model the main independent variable as an interaction effect measuring the
combined influence of gender and method of election. This allows for comparisons of
qualifications between female PR representatives and male PR representatives, female
SMD representatives, and so on.
Because all of the quota women in our sample come from the PR seats, and all of
the non-quota women from the SMD seats, we pay careful attention to potential
5
This is significantly below 50%, the proportion one might have expected women to obtain from the
required alternation of genders on the closed party lists. As it turns out, the parties that could only nominate
one or two individuals on the list would often place the male candidate first (Katz, 1996). In addition, the
decision of party elites to nominate women in non-winnable districts affected the final percentage of women
elected via the PR quota.
6
For example, parties might nominate stronger candidates in SMDs where personal attributes are
thought to matter more (Carey and Shugart, 1994). The existence of the scorporo rule in Italy’s electoral
system, which subtracts a portion of the SMD winners’ votes from the party list’s votes, might also affect
party strategies (although exactly how it might affect overall quality in each group is not obvious).

differences between legislators in the two tiers.7
Any differences between quota
women and non-quota women could be the result of the electoral system rather than
the quota law. For example, SMD races tend to be more hotly contested and high
profile than closed-list PR races, so parties are more likely to nominate stronger
candidates in the SMDs or open-list PR where personal attributes and/or connection
to constituents matters more than party loyalty (Carey and Shugart, 1994; Shugart
et al., 2005). Mixed electoral systems have also been found to encourage legislators
to specialize in different areas: those elected through the nominal vote focus on
representing geographic constituencies, while those elected through the list heed the
priorities set by party leaders (Shugart, 2001; Gagliarducci et al., 2011). If these
claims are true, we should expect to find significant differences between candidates
(both men and women) elected in the majoritarian tier and those elected via PR list.
In general, we would expect those elected in SMDs to be more qualified.
Data and methods
We use data on all members of the Italian Camera dei Deputati (House of Repre-
sentatives) who were elected in the general election of 1994 (12th legislative term),
collected by Gagliarducci et al. (2008, 2011). The data set contains a wealth of
information including self-declared demographic characteristics (age, gender, level
of education, previous job, and marital status); past and current political experience
in elections and party appointments at the local, regional, and national level; past
and current appointments in government and parliament; income information from
the year before election; information on bills proposed as main sponsor; absences in
floor voting sessions without any legitimate reason; and data on re-election.8
Table 2 provides a complete list of all variables used in the analysis, as well as
summary statistics.
The key independent variable in our analysis is quota women, which is oper-
ationalized as the interaction between female gender and being elected in the pro-
portional tier of the electoral system, where the quota was implemented
(Female*PR). We compare quota women to non-quota women, those elected in the
majoritarian tier. This is the main comparison group we are interested in testing.
7
Representatives in the (closed list) PR system relied on party loyalty to be nominated and elected, while
representatives in the SMD system relied on party loyalty but also personal reputation and constituency
service. Party leaders had complete control over PR candidates’ inclusion and ranking on the party lists,
unlike in open list or preference vote systems (Ferrara, 2004). Candidates could run in both systems, but if
they won a SMD seat they had to accept it. If they lost in the SMD election, they could still be elected in the
PR system if they were ranked high enough on the party list. This distinction was clear to voters: candidates
elected in the SMD system were seen as a representative of that constituency and asked to provide con-
stituency services, whereas candidates elected in the PR system were perceived to be party leaders, likely to
serve in government or parliament appointments (Gagliarducci et al., 2011).
8
The original sources of the data were individual biographies for personal details, the Parliament Press
office for data on voting absences, the Parliament Tax Declarations Archive for data on income, and the
Parliament website for data on bills.

Table 2. Summary statistics, Italian members of parliament 1994–96
Variable Mean std. dev. Range
Female 0.15 0.35 0–1
PR 0.25 0.43 0–1
Age 47.04 9.93 27–84
Government/parliament appointment 0.34 0.47 0–1
Past party appointment 0.34 0.47 0–1
Higher education 0.68 0.46 0–1
Pre-election Income (€1000s) 85.01 356.81 0.2–8393
National government experience 0.30 0.46 0–1
Local government experience 0.47 0.50 0–1
Number of bills proposed 4.95 7.42 0–95
Absentee rate 0.38 0.20 0.02–0.98
Re-election 0.69 0.46 0–1
Political party (electoral list)
Forza Italia 0.22 0.42 0–1
Lega Nord 0.19 0.39 0–1
Alleanza Nazionale 0.17 0.38 0–1
Partito Democratico della Sinistra 0.13 0.34 0–1
Alleanza Democratica 0.07 0.26 0–1
Rifondazione Comunista 0.06 0.24 0–1
Partito Popolare Italiano 0.05 0.22 0–1
Partito Socialista Italiano 0.03 0.18 0–1
Federazione dei Verdi 0.03 0.17 0–1
Patto di Rinascita Nazionale - Patto Segni 0.02 0.14 0–1
Other 0.01 0.10 0–1
Parliamentary party
Progressisti-Federativo 0.26 0.44 0–1
Forza Italia 0.18 0.38 0–1
Lega Nord 0.18 0.38 0–1
Alleanza Nazionale 0.17 0.38 0–1
Rifondazione Comunista 0.06 0.24 0–1
Partito Popolare Italiano 0.05 0.22 0–1
Misto-altro 0.05 0.22 0–1
Centro Cristiano Democratico 0.04 0.20 0–1
Previous job
Lawyer 0.12 0.33 0–1
Entrepreneur 0.11 0.31 0–1
Self-employed 0.11 0.30 0–1
Teacher 0.10 0.30 0–1
Journalist 0.09 0.28 0–1
Physician 0.09 0.29 0–1
Professor 0.09 0.29 0–1
Manager 0.06 0.24 0–1
Bureaucrat 0.05 0.22 0–1
Professional politician 0.05 0.23 0–1
White-collar 0.05 0.22 0–1
Magistrate 0.02 0.16 0–1
Trade Union Representative 0.01 0.10 0–1

Without the gender quota, we would expect all women elected to have similar
qualifications for office.
We operationalize our measures of qualifications for office as follows: (1) Higher
Education, a binary variable coded 1 if the legislator reported having a Bachelor’s
degree or above, and 0 otherwise; (2) Pre-election Income, a continuous variable mea-
suring occupational achievement, from tax returns measured in 2005 Euros; (3) National
Government Experience, a binary variable coded 1 if the legislator previously served
in the Chamber of Deputies, and 0 otherwise (4) Local Government Experience,
a binary variable coded 1 if the legislator previously served in local government (mayor
or councilor), and 0 otherwise. Following recent studies, we use income as a measure of
occupational achievement and overall status because it reflects the market value of an
individual’s ability or skills (e.g., Gagliarducci et al., 2008).9
One obvious problem with
using national-level political experience for our purposes is its correlation with gender.
An average of 6.5% women served in the Italian national parliament from 1946 to 1994;
a consistently low percentage of women in office is precisely what prompted support for
gender quotas in the first place. Thus, we would expect women, and quota women in
particular, to have lower levels of national level experience compared with men.
We explore the similarities and differences between quota women, non-quota
women and men once they are in office using three measures of legislative behavior:
(1) Bills Proposed, a count variable for the number of bills the legislator proposed as
primary sponsor over the legislative term; (2) Absentee Rate, the percentage of votes
for which the legislator was absent; and (3) Re-election, a binary variable for
whether the legislator won re-election to the next legislative term, conditional on the
legislator running.
In the following section we examine the relationship between quota women and
our measures of qualifications and quality. First, we use bivariate analysis to answer
the question of whether quota women and non-quota women differ on the measures
we care about. Specifically, we use χ2
goodness of fit tests for binary variables
(Higher Education, National Government Experience, Local Government
Experience, and Re-election) and t-tests for other variables (Pre-election Income,
Bills Proposed and Absentee Rate). We next turn to the question of determinants of
legislator qualifications and quality more broadly. What predicts or explains qua-
lifications, and do gender quotas have a negative impact? We use multivariate
analysis because it allows us to control for other factors that may be correlated with
gender, such as previous job or incumbency. The first set of regressions assesses
determinants of qualifications for office, and the second set explores determinants of
quality once in office. Because our key independent variable is an interaction term
(Female*PR), the constituent terms Female and PR in our regression models should
be interpreted as women elected in SMDs, and men elected in PR seats, respectively.
9
The Gagliarducci, Nannicini, and Naticchioni data are gross individual income declared in year 1 of
the term (which refers to the previous fiscal year), collected from the Parliament Income Tax Declarations
Archive.

We are interested in testing whether women who are elected as a result of gender
quotas (and who, presumably, would not have been elected otherwise) are as qua-
lified as their counterparts. We consider their most comparable counterparts to be
women elected without the aid of a quota in the majoritarian tier. The key statistic
we use to assess whether quota women are different from non-quota women is thus
a Wald χ2
test that measures the significance of differences between the two coeffi-
cients Female and Female*PR. Because ‘quota women’ is operationalized as an
interaction term in our data (Female*PR), the regression models do not provide us
with clear estimates of the marginal effects of female gender or method of election
on qualifications. We provide this using ‘first differences’ in expected values.10
First
differences are calculated from a counterfactual simulation (N = 1000), where a
legislator typical in all respects is assumed to change the column variable from its
minimum to its maximum (e.g. from a non-quota woman to a quota woman). They
give us a measure of the magnitude of the effect of each key variable estimated in the
models on the scale of the dependent variable (King et al., 2000).
As previously discussed, any differences between quota- and non-quota women
could be due to their different method of election rather than the quota law. We are
able to address this issue by including Wald χ2
test statistics measuring the sig-
nificance of differences between the coefficients for men and women elected in the
same system. We also provide the marginal effects of PR method of election along
with other quantities of interest, including female gender and quota women. In
order to convey the average effects of our quantities of interest, most importantly
the effect of being a quota woman, we illustrate the distributions of simulated first
differences in expected values in Figure 3. We provide the numeric values in Table 6.
We control for other background characteristics where appropriate, including
Age, Incumbency, Electoral Political Party, Parliamentary Group, Previous Job,
and Government/Parliament Appointment.11
In the analysis of quality (perfor-
mance in office), we also control for Education, Pre-election Income, National
Government Experience, and Local Government Experience. These variables may
be linked to gender and our measures of qualifications and/or quality, and so we
account for them in the model(s) in order to avoid detecting spurious relationships.
In general, we expect Age and Incumbency to have a positive ‘effect’ on qualifi-
cations/performance. We expect Higher Education to have a positive impact on
pre-election income and measures of performance. We also expect Pre-election
Income and Local Government Experience to have a positive effect on measures of
performance if qualifications for office should be correlated with quality of
10
Including marginal effects also deals with the problem of interpreting the coefficients of probit (Higher
Education, National Government Experience, Local Government Experience, and Re-election) and negative
binomial (Bills Proposed) regression models, which have little substantive meaning in themselves.
11
Government/Parliament Appointment indicates appointment to a position within the government or
parliamentary group of the current legislature. Appointment in government is coded 1 if the individual is
president, vice president, minister, or vice minister in government (self declared). The figures for Electoral
List in Table 2 include both PR and SMD candidates.

performance in office. We expect Government/Parliament Appointment to have a
positive effect on performance measures because these representatives have worked
their way up in the party and are likely to hold certain responsibilities, like intro-
ducing key bills to the parliament. We control for Previous Job only in the regres-
sion on Pre-election Income because certain types of jobs are correlated with
particular income bands and gender. Finally, we expect Electoral Political Party and
Parliamentary Group variables to have different impacts depending on the party.
Electoral Political Party refers to the political party affiliation on the candidate list,
while Parliamentary Group refers to the group affiliation once in office; the two are
sometimes the same. We control for Electoral Political Party when measuring
determinants of candidate qualifications, and Parliamentary Group when measur-
ing determinants of legislator performance.12
We would expect members of
the Communist party to have a negative effect on higher education and income
because of the party’s traditional recruitment of working-class candidates (Cotta
and Verzichelli, 2007). However, Forza Italia was known for recruiting business
professionals for their managerial experience (Newell, 2010), so we would expect FI
membership to have a positive impact on these measures of qualification.
For the dependent variables Pre-election Income and Absentee Rate, we use
ordinary least squares regression, transforming pre-election income by the loga-
rithmic function to ensure that extreme incomes do not play a disproportionate
role [Log (Pre-election Income)]. For the dependent variables Higher Education,
National Government Experience, Local Government Experience, and Re-election
we estimate probit regression models because the outcomes are binary. For the
dependent variable Bills Proposed, we use negative binomial regression because the
outcome is a count.13
The sample for the regression on Re-election includes only
those representatives who stood for re-election (456 of the 630 representatives).
We are not able to distinguish the reasons why some representatives, including
14 of 50 quota women, did not run for re-election. We note that the percentage of
quota women who ran for re-election is exactly the same percentage of repre-
sentatives who ran for re-election overall – 72%.
Analysis
How do the women representatives elected under the 1993 quota law compare to non-
quota female and male representatives? If either the quota law or the type of electoral
12
The data on electoral party affiliation are from the Camara dei Deputati website (http://legislature.
camera.it/frameset.asp?content=%2Faltre_sezionism%2F10247%2F10261%2Fdocumentotesto%2Easp
%3F) and specifically from the ‘Deputati’ link at the top left of that page. We obtained ‘Lista di elezione’ by
clicking on the page for each individual legislator.
13
A likelihood ratio test for overdispersion comparing Poisson and negative binomial models strongly
suggests that the negative binomial model is more appropriate than the Poisson model (χ2
= 2029.1). The
model is not zero-truncated because every representative has the opportunity to propose bills, and most
propose one or more.

system impacts the selection of female candidates, we would expect the initial bivariate
analysis to show significant differences between quota- and non-quota women.
On most of our measures, we find no significant difference between quota women
and non-quota women. Table 3 reports the mean values for quota women and
non-quota women, and the P-value for associated χ2
and t-tests.14
While we find
evidence of some differences, none of them is statistically significant. A smaller
percentage of quota women have achieved a degree in higher education (Bachelor’s
level and above) than non-quota women, but this difference is not statistically sig-
nificant. A greater percentage of non-quota women have experience in local and
national government. This provides some evidence either toward the theory that
candidates elected via SMD will be more invested in their constituency, or toward
the theory that quota women will be less experienced. We note that the differences
are not statistically significant. Quota women propose fewer bills than non-quota
women on average and are less likely to be re-elected, but these differences are not
statistically significant. On the other hand, pre-election income is slightly higher
for quota women compared with non-quota women, and quota women also have
lower absentee rates than non-quota women on average (differences are not
statistically significant).
Figure 2 shows the standardized difference in means between quota women and
non-quota women, with 95% confidence intervals. The standardized difference in
Table 3. Comparison of quota women and non-quota women
Quota women Non-quota women P-value
N 50 42
Mean higher education (0 or 1) 0.64 0.73 0.31
Mean pre-election income (€100s) 45.69 42.68 0.65
Mean national government experience (0 or 1) 0.26 0.31 0.77
Mean local government experience (0 or 1) 0.30 0.45 0.13
Mean number of bills proposed 4 7.5 0.13
Mean absentee rate 0.30 0.32 0.50
Mean re-election (0 or 1) 0.71 0.85 0.16
Notes: P-values are for a Pearson χ2
goodness of fit test (with Yates’ continuity correction) when
the variable is binary, or Welch Two Sample t-test (when the variable is continuous or count).
Both test the hypothesis that proportions are the same for quota women and non-quota women.
Analysis was carried out in R.
14
We use two-tailed t-tests, which test the hypothesis that quota women and non-quota women are
equally qualified. Some might argue that a one-tailed test, which tests the hypothesis that quota women are
less qualified than non-quota women, is more appropriate. We calculated the P-values for one-tailed t-tests
for all variables, and find no substantive changes to our results. The biggest change is in the hypothesis test
on mean Number of Bills Proposed, which becomes significant at the 0.10 level, but not at the standard 0.05
level (P = 0.07).

means is the difference in the mean value for quota women and the mean value for
non-quota women, divided by the standard deviation for quota women. It converts
the average differences between the groups to a common scale, so they can all be
plotted on the same axis and compared. Every confidence interval bar in the chart
crosses 0, showing that although there are average differences between quota and
non-quota women, none is statistically significant.
Multivariate analysis allows us to compare quota women and non-quota women
to their male counterparts. We begin with ex ante qualifications. Table 4 presents
the results of four separate models that estimated the effect of quotas on three
aspects of representative characteristics. Model (1) tests the hypothesis that quota
women are less educated than non-quota women or men. Model (2) examines the
impact of gender and quotas on average pre-election income, controlling for pre-
vious job. This model tests the hypothesis that quota women held lower status jobs
than non-quota women or men. Finally, models (3) and (4) test the hypothesis that
gender quotas increase the number of legislators who have less previous national
and local political experience, respectively.
The results of model (1) show that women, whether elected with the aid of a
gender quota or not, do not differ from men in terms of overall educational quali-
fications. The top left distribution in Figure 3 is a simulation of the expected values
of achieving higher education for different types of legislators. The dotted line
Figure 2 Standardized differences between quota women and non-quota women.

shows the expected difference when we move from a legislator who is not a quota
woman to one who is a quota woman (i.e. the value of Female*PR from 0 to 1). The
broken line represents all men and women elected in the PR tier and the solid line
represents all women (quota- and non-quota women combined). The associated
vertical lines represent the mean first difference in expected value (also reported in
Table 6). In the case of education, we can see that all the distributions are centered
around zero, indicating that quotas have no impact on level of education – nor does
gender or being elected in a PR seat.15
Model (2) demonstrates that, when controlling for previous job, income for
quota women (our measure of occupational status) does not differ from that of
other legislators. The marginal effect of female gender and quota women on earn-
ings is shown in the top middle panel of Figure 3. The parallel distributions for
female legislators and quota women show the similarity of differences in expected
Table 4. Determinants of legislator qualifications
(1) Higher
education
(2) Log (pre-election
income)
(3) National
government
(4) Local
government
λ Female*PR
(quota woman)
− 0.36 (0.33) − 0.20 (0.20) − 1.04 (0.35)** 0.15 (0.32)
α Female (non-quota
woman)
0.27 (0.23) − 0.24 (0.16) 0.29 (0.23) − 0.15 (0.22)
γ PR 0.02 (0.17) 0.14 (0.11) 0.72 (0.17)*** − 0.65 (0.16)***
Constant − 0.26 (0.54) 2.32 (0.38) − 1.89 (0.69) 0.08 (0.52)
N 630 630 630 630
P-value, test (α = λ) 0.21 0.89 0.01 0.54
P-value, test (λ = γ) 0.37 0.22 0.00 0.06
Adjusted R2
0.31
χ2
31.14 173.79 101.62
Controls for previous
job
No Yes No No
Notes: White-corrected standard errors are in parentheses. Models (1), (3), and (4) are estimated
using probit regression and model (2) is estimated using ordinary least squares regression.
Previous job controls are dichotomous variables indicating occupational background, including
lawyer, bureaucrat, journalist, teacher, physician, magistrate, professor, entrepreneur,
white-collar, self-employed, and retired. All models include controls for age and electoral
political party. Model (2) also includes controls for national government experience and higher
education. Model (3) includes controls for local government experience and past party
appointment, and model (4) includes controls for national government experience and past
party appointment. All analyses were carried out using Zelig for R (Imai et al., 2008).
Significant codes: ***0.001; **0.01; *0.05.
15
To test the robustness of our findings, we also ran a regression using an ordinal dependent variable
for level of education, where 1 = primary school education and 5 = Masters degree or higher (specifying an
ordinal probit model). Our results do not change substantively. Age remains the only significant predictor of
educational background.

values of income for being a woman, regardless of method of election. Women
elected in both tiers are expected to have lower pre-election income compared
with men, although the difference is not statistically significant. This link does not
surprise us, given the persistent gender gap in income. As of 2003, Italian
women’s salaries were 74% of men’s, a figure that was probably lower in 1993
(ISTAT, 2003).
Model (3) shows that, as we expected, quota women are less likely to have
experience in national office compared with non-quota women and their male peers
in the PR tier. A test of the coefficients Female*PR and Female suggests that the
difference between quota- and non-quota women is significant (P = 0.01), and a
Figure 3 First differences of quota women on qualifications and quality.
Notes: Figures show density plots of the simulated first differences reported in Table 6, with the
corresponding vertical bars indicating the mean first difference in expected values for each type
of legislator.

similar test also finds the difference between quota women and their male colleagues
in the PR tier to be significant (P = 0.00). The density plot in the top right panel of
Figure 3 shows that quota women are associated with a 22% decrease in national
government experience, while women in general are associated with a 10% increase
(although this is not significant at standard levels). This finding does not surprise us
because the very reason many give for adopting quotas is the paucity of women who
manage to reach national office. We turn to our alternative measure of previous
experience, service in local government, to explore whether this relationship
extends to other characterizations of political capability.
Model (4) indicates that there is a significant relationship between men elected in
the PR tier and previous local government experience. Male PR candidates are less
likely to have previous experience serving in local government compared with their
SMD peers. However, the coefficient for quota women is positive and not sig-
nificant, and a test of the two coefficients Female*PR and PR indicates that the
difference between the two is significant at the 0.10 level (P = 0.06). That is, the
negative relationship between method of election and local experience is significant
only for male representatives. This finding confirms previous studies that show that
politicians elected in PR systems are less likely to have strong local ties than those
elected in SMDs (Gagliarducci et al., 2011). The first differences reported in Table 6
(and shown in Figure 3) provide a substantive measure of the magnitude of this
effect. Representatives (both men and women) elected in the proportional tier are
24% less likely to have local government experience than legislators elected in SMD
seats. However, women elected in the proportional tier (quota women) are 5%
more likely to have local government experience than other representatives. If we
assume that in the absence of a quota law more men would have been elected in the
PR tier, this finding suggests that quota women may have improved the overall level
of qualifications.
Next, we turn to legislative behavior, which we consider as a measure of ex post
qualifications. How does the average performance of quota women in office com-
pare to that of non-quota women and men? Table 5 presents the results of the
models estimating the impact of various legislator characteristics on overall quality.
We present three separate models to test three different measures of legislative
behavior. Model (5) tests the hypothesis that quota women propose fewer bills than
non-quota women or men. Model (6) tests the hypothesis that quota women are
more likely to shirk their political duties than other representatives, measured in
terms of attendance at legislative sessions. Finally, model (7) tests the hypothesis
that quota women are less likely to win re-election, which is of course conditional
on their running in the next election. Table 5 shows that quotas have a significant
impact on two out of three measures of representative quality. Quota women do not
differ from their peers in terms of bill introductions, but they do have lower rates of
absenteeism and are associated with lower re-election rates.
Model (5), a regression of number of bills proposed, finds that the PR method of
election is again associated with negative quality, but quota women do not differ

from men elected in the PR tier. Representatives elected by PR propose just over one
less bill per legislative term compared with other representatives (Table 6). A Wald
test of the difference between Male*PR and PR coefficients was not significant,
indicating that we cannot reject the hypothesis that quota women are significantly
different from their male PR peers on this measure of performance. The density
plots shown in Figure 3 illustrate that the distribution of expected values of bills
proposed is similar for quota women and all those elected in the PR tier.
Model (6) finds that men elected in the proportional tier have higher rates of
absenteeism than others. Compared with other legislators, PR elected legislators are
associated with a 5% increase in the absentee rate (see Table 6). However, quota
women are associated with a significant decrease in absenteeism. A Wald test of the
difference between PR and Female*PR coefficients is significant, suggesting that the
difference between quota women and men elected in the PR tier is significant
(P = 0.04). The density plots at the bottom of Figure 3 show that quota women are
associated with a 7% decrease in absenteeism (female members in general are
associated with a 1% decrease, although this is not significant at standard levels).
This finding adds another piece of evidence suggesting that, contrary to critics,
quota laws may have a positive impact on legislator quality.
Our last model of legislator quality, model (7), considers the relationship between
personal characteristics and the likelihood of re-election. In some ways, this is
perhaps the best measure of legislator quality: do political parties and voters
Table 5. Determinants of legislator quality
(5) Bills proposed (6) Absentee rate (7) Re-election
λ Female*PR (quota woman) − 0.12 (0.29) − 0.08 (0.04)* − 1.22 (0.50)**
α Female (non-quota woman) 0.27 (0.19) − 0.01 (0.03) 0.75 (0.38)
γ PR − 0.28 (0.14)* 0.05 (0.02)* 0.38 (0.23)
Constant 2.44 (0.37) 0.39 (0.07) 0.30 (0.69)
N 630 599 456
P-value, test (α = λ) 0.36 0.35 0.02
P-value, test (λ = γ) 0.68 0.04 0.01
McFadden’s pseudo R2
0.39
Adjusted R2
0.21
χ2
88.04
Notes: White-corrected standard errors are reported in parentheses. Model (5) is estimated using
negative binomial regression, model (6) is estimated using ordinary least squares regression, and
model (7) is estimated using probit regression. The sample for model (7) includes only those
representatives who ran for re-election. The sample for model (6) is smaller due to missing data in
the dependent variable. All models include controls for age, national government experience,
higher education, log (pre-election income), local government experience, appointment in
government or parliament, and electoral political party (models 5 and 6) or parliamentary party
(model 7). All analyses were carried out using Zelig for R (Imai et al., 2008).
Significant codes: ***0.001; **0.01; *0.05.

Table 6. Marginal effects of quota women on qualifications and quality
(1) Higher education
(2) Log(pre-election
income)
(3) National govern-
ment experience
(4) Local government
experience (5) Bills proposed (6) Absentee rate (7) Re-election
Female*PR
(quota
woman)
− 0.14 ( − 0.38, 0.09) − 0.20 ( − 0.58, 0.20) − 0.22 ( − 0.29, − 0.10) 0.05 ( − 0.18, 0.28) − 0.35 ( − 2.28, 2.25) − 0.07 ( − 0.16, 0.01) − 0.43 ( − 0.72, − 0.07)
Female (all
women)
0.08 ( − 0.06, 0.21) − 0.24 ( − 0.56, 0.07) 0.10 ( − 0.06, 0.26) − 0.06 ( − 0.22, 0.10) 1.51 ( − 0.35, 3.89) − 0.01 ( − 0.06, 0.05) 0.16 (0.00, 0.26)
PR (men and
women)
0.01 ( − 0.01, 0.12) 0.14 ( − 0.08, 0.35) 0.26 (0.13, 0.38) − 0.24 ( − 0.36, − 0.12) − 1.10 ( − 2.12, 0.02) 0.05 (0.01, 0.10) 0.10 ( − 0.02, 0.22)
Notes: Significant effects are in bold. Cells give the estimated change in probability or predicted values (for the negative binomial model (4)) that comes from a counterfactual simulation
(N = 1000), where a legislator typical in all respects is assumed to change the column variable from its minimum to its maximum, for example from not a quota woman to a quota woman.
First differences were simulated from models reported in Tables 4 and 5; 95% confidence intervals for the changes in probability are given in parentheses. First difference effects are estimated
using the Zelig package for R (Imai et al., 2008).
Quotasandqualifications137

want to re-invest in the legislator, or do they want to kick them out? Recall that
voters had two votes in Italy’s mixed system: one for a candidate in a SMD and one
for a political party represented by closed regional lists. Those elected in the
majoritarian seats are thus assessed by their party for re-nomination in a good
district and by constituents who vote for them directly, while those elected in the
proportional seats mainly look to their political party for good placement on the list
in a safe district.
Model (7) finds that quota women are less likely to be re-elected compared with
other legislators. Again, this model includes a sample of only those legislators who
chose or were selected to run for office in the subsequent election. A Wald test of the
difference between PR and Female*PR coefficients is significant, suggesting that the
difference between quota women and men elected in the PR tier is significant.
Similarly, a test of the difference between Female and Female*PR coefficients is
significant, suggesting that the difference between quota women and women elected
in SMDs is significant. Both men in the PR tier and women elected in SMDs
are more likely to be re-elected (the baseline group left out being men elected in
SMDs). Marginal effects presented in Table 6 show that quota women are 43% less
likely to be re-elected compared with other representatives running for re-election
(men and women).
The finding for quota women is important because the quota law was no longer in
effect when representatives were running for re-election. Our results suggest that
when the quota was removed, parties placed quota women in less winnable posi-
tions. This observation is consistent with Folke and Rickne (n.d.) finding that male
incumbents protect their own careers by limiting the re-election of female legisla-
tors, but runs contrary to Bhavnani’s (2009) findings about the withdrawal of
quotas in India. Further research is needed to illuminate decision-making processes
and to understand better the impact quota laws have on candidate selection after
the law is removed.
Our findings are robust to alternative definitions of who counts as quota women.
Perhaps incumbent females elected in the PR portion should not be considered part
of the quota cohort. We identified all incumbents in 1994 re-elected in the PR tier,
dropped them, and re-ran our analysis for a sample of newcomers only (the total
sample dropped from 630 to 439, a number which is still large due to the high
turnover in 1994). Our results do not change substantively (see Appendix B online
for full results). The bivariate analysis shows that quota women are less likely to be
re-elected and have less previous experience in local government, but the differences
are not statistically significant. The multivariate analysis again finds that quota
women do not have a negative impact on local government experience, while their
male peers in the PR tier do. A Wald test of the difference between quota women
and men elected in the PR tier is significant at the 10% level in this model. Quota
women have a negative impact on absenteeism (here the test of the difference
between coefficients for quota women and PR men is significant at the 5% level),
and are less likely to be re-elected (again, associated Wald tests are significant).

Women who were first on their PR list might also not be considered quota
women. We identified all women who were first on their PR lists in 1994.16
Ten
of the 50 women were first on their list (compared with 67 of the 105 men elected
via PR). We dropped these 10 women from the sample and re-ran the analysis.
Again there were no substantive changes to our results (see Appendix C online for
full results). The bivariate analysis finds that quota women are less likely to be
re-elected compared with non-quota women, significant at the 0.10 level (P = 0.07).
None of the other differences approach statistical significance. The multivariate
analysis confirms that quota women do not have a negative impact on local
government experience, while their male peers in the PR tier do (the difference is
significant, P = 0.03). Again, quota women are associated with less absenteeism (and
the test of the difference between coefficients for quota women and PR men is
significant), and are less likely to be re-elected (associated Wald tests between quota
women and PR men, and quota women and non-quota women, are significant).
Conclusion
Our aim in this article was to subject to empirical analysis claims that candidates
nominated on the basis of gender quotas will be less qualified to serve in legislative
office. We examined this claim through a case study of Italian legislators. Our
analysis shows that, contrary to the concerns of quota opponents, quota women are
not less qualified than men or than other women in terms of education, occupa-
tional achievement, or previous political experience at the local level. Legislators
elected in the PR portion of Italy’s mixed system are less likely to have previous
experience in national office – but this is not surprising given women’s historic
underrepresentation in Italian politics. Our analysis of ex post legislative quality
reiterates these findings, demonstrating that quota women are just as likely to
propose bills and more consistent in attending sessions of parliament. However,
they are less likely to win re-election compared with their peers, a factor we provi-
sionally attribute to the removal of the quota in the subsequent election. This finding
suggests that the lower percentage of women in office can be attributed to dis-
crimination against them by party leaders. Re-election may not be a fair or accurate
measure of candidate quality in cases where party leaders act as gatekeepers for
candidate selection, placement in a winnable district, and list ranking.
We defined qualifications according to conventional standards used most often in
the political science literature: level of education, professional achievement, and
previous political experience. We also consider behavior in office as a measure of
qualifications. In this study, we take the term ‘qualifications’ at face value and define
and measure it according to the way that most political scientists do – and, perhaps,
the way most people do in everyday language. At the same time, we realize that in
relying on a conventional standard of qualifications, we may also be relying on a
16
List placement information from the Italian Ministry of the Interior: www.interno.it.

‘male’ standard of qualifications. We heed the caution offered by Franceschet et al.
(2012) about how to define qualifications when it comes to gender quotas. We
acknowledge that our approach does not account for the kinds of characteristics
where women may be more likely to have an advantage over men, such as partici-
pation in non-governmental organizations or other non-partisan forms of political
participation. We suspect that when people object to gender quotas on qualifica-
tions grounds, what they oppose, usually without saying so, is making gender itself
a qualification for office. In a sense, gender does become a formal qualification for
office with the adoption of gender quotas (Rehfeld, 2009).
Questions about quotas and qualifications remain relevant in Italy. In 2003, the
legislature passed a constitutional amendment allowing affirmative action to
increase women’s presence in elected bodies, but legislators have not yet acted on
this opportunity to reintroduce legislative quotas (Guadagnini, 2005). In 2010, a
bill requiring a 30% quota for women on all corporate boards inspired the same
type of zero-sum rhetoric about quotas and qualifications as the 1993 legislative
quota did. In letters to the editors of major Italian newspapers, citizens argued that
‘I got my position on my own merits’ (Corriere della Sera, July 5, 2011); that ‘gender
quotas are offensive to the women who fought and are fighting for parity on the
basis of their capacity and their merit’ (La Stampa, March 11, 2011); and even that
‘we need a quota for brains, not sex’ (La Nazione, March 8, 2011).17
The corporate
board bill also split the conservative Popolo della Libertá (Pdl) party (successor to
Forza Italia) along gender lines, with many male party members coming out against
the quota while female members supported it. The bill was passed into law on
June 28, 2011.
The lessons learned in this study have implications beyond the scope of Italy.
Gender quotas remain a popular policy option throughout the international com-
munity. Our results offer some leverage in addressing one of the most common
arguments against quotas and warrant further testing against data from other cases.
One avenue for future research is to expand this research to other countries with
mixed electoral systems in which a quota applies only to the PR seats. Promising
cases include Armenia, Bolivia, Ecuador, Honduras, Korea, Mauritania, Panama,
and Senegal. Our results also suggest broader implications for questions about the
impact of electoral rules on candidate selection. According to this research, rules
that restrict candidate selection reduce the quality of candidates, while rules that
open up selection, such as primaries, generate candidates with higher qualifications.
Our study shows this trend does not hold when the electoral rule concerns the
selection of a marginalized group, in this case women. Even though quota laws restrict
competition, they do not necessarily result in lower quality candidates being elected.
One hypothesis is that political parties, the main gatekeepers to elected office in
systems of proportional representation, do not always choose the most qualified
17
All translations are our own.

candidates. While this is the intuition behind the literature suggesting that restricting
competition leads to lower quality candidates, quota laws force parties to change
their behavior and thus constitute a different type of restriction. In fact, quotas can be
viewed as opening up political competition for specific underrepresented groups.
On the supply-side of the political marketplace, plenty of qualified women may
want to pursue a political career, and on the demand side of the equation plenty of
voters might be willing to support them. If parties do not support female candidates
(because of implicit bias or discrimination by party leaders), the explanation for
women’s underrepresentation rests with a block in the supply that prevents women
from being part of the candidate pool in the first place. Quota laws can overcome
this block by forcing parties to change their behavior and select more women.
Further research could test this hypothesis by comparing the outcomes of affirma-
tive action policies in countries with varying levels of supply and demand for female
candidates. We would expect our results to hold in cases where there is good reason
to think the supply is there (e.g. women have access to educational and professional
opportunities) and voter demand is relatively high, suggesting supply-side obstacles
(i.e. the party selectorate) prevent women from entering politics rather than the
supply of women or voter demand.
Supplementary material
To view supplementary material for this article, please visit http://dx.doi.org/
10.1017/S1755773914000095
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